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 # LLaMA-Adapter: Efficient Fine-tuning of LLaMA 🚀
 
-## Announcement: We release **[LLaMA2-Accessory](https://github.com/Alpha-VLLM/LLaMA2-Accessory)**, an open-source toolkit for **pre-training**, **fine-tuning** and **deployment** of **LLMs** and **mutlimodal LLMs**.🔥
+## Announcement: We release **[LLaMA2-Accessory](https://github.com/Alpha-VLLM/LLaMA2-Accessory)**, an open-source toolkit for **pre-training**, **fine-tuning** and **deployment** of **LLMs** and **multimodal LLMs**.🔥
 
 Official implementation of ['LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention'](https://arxiv.org/pdf/2303.16199.pdf) and ['LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model'](https://arxiv.org/pdf/2304.15010.pdf).
 
@@ -14,7 +14,7 @@ Try out the web demo 🤗 of LLaMA-Adapter: [![Hugging Face Spaces](https://img.
 
 ## News
 - **[2023.08.28]** We release quantized LLM with [OmniQuant](https://github.com/OpenGVLab/OmniQuant), which is an efficient, accurate, and omnibearing (even extremely low bit) quantization algorithm. Multimodal version is coming soon.🔥🔥🔥
-- **[2023.07.24]** We release **[LLaMA2-Accessory](https://github.com/Alpha-VLLM/LLaMA2-Accessory)**, an open-source toolkit for **pre-training**, **fine-tuning** and **deployment** of **Large Language Models (LLMs)** and **mutlimodal LLMs**. Please check [Alpha-VLLM/LLaMA2-Accessory](https://github.com/Alpha-VLLM/LLaMA2-Accessory) for more details!🔥🔥🔥
+- **[2023.07.24]** We release **[LLaMA2-Accessory](https://github.com/Alpha-VLLM/LLaMA2-Accessory)**, an open-source toolkit for **pre-training**, **fine-tuning** and **deployment** of **Large Language Models (LLMs)** and **multimodal LLMs**. Please check [Alpha-VLLM/LLaMA2-Accessory](https://github.com/Alpha-VLLM/LLaMA2-Accessory) for more details!🔥🔥🔥
 - **[2023.07.05]** We release the pretrain/finetune code of [llama_adapter_v2_multimodal7b](https://github.com/OpenGVLab/LLaMA-Adapter/tree/main/llama_adapter_v2_multimodal7b).
 - **[2023.07.04]** We release the code for reproducing [Gorilla](https://github.com/ShishirPatil/gorilla) by both full finetune and LLaMA-Adapter, please see [gorilla/README.md](https://github.com/OpenGVLab/LLaMA-Adapter/blob/main/gorilla/README.md).
 - **[2023.06.08]** We release the [demo](http://imagebind-llm.opengvlab.com/) of ImageBind-LLM.